Systems | Development | Analytics | API | Testing

As I recently transitioned to Qlik's Professional Services team to lead Advisory Services, I embraced a clear mission: to engage in high-level discussions with business stakeholders that drive faster value and enhance your return on investment (ROI). By employing a structured 10-step approach grounded in a repeatable agile methodology, we are actively enabling out customers to overcome challenges and achieve their strategic objectives.

Apache Parquet has become the de-facto standard for storing data used in analytics workloads, and has seen very broad adoption as a free and open-source storage format. When used as the underlying storage layer for Apache Iceberg, Parquet is also a foundational building block in modern lakehouse architectures, which enable warehouse-like capabilities on cost effective object storage. Let’s take a closer look at what Parquet actually is, and why it matters for big data storage and analytics.

Some data problems are universal — like dealing with unstructured data. At Bystronic, a global leader in sheet metal processing, we have mountains of it. From technical documentation to sales decks, HR policies, and IT knowledge bases, data is scattered across folders, servers, and systems. Industry research shows that 80% of enterprise data is unstructured, meaning it’s often invisible to the teams that need it most. As a result, up to 68% of that data goes unused. The impact is real.

Over the first half of this year, I’ve had the unique privilege of traveling across EMEA, APAC, and the US, leading our global Agentic AI workshop series. From London to Singapore to Mumbai, I’ve had a front-row seat to how enterprises—across industries and continents—are rethinking what software can be in an age of intelligent systems. And I can confidently say: the era of Agentic AI has arrived.

At Qlik, we’re incredibly proud of our Luminary and Partner Ambassador communities. They’re more than customers, more than partners, they’re an integral part of who we are. For over a decade, hundreds of data leaders across industries and continents have proudly called themselves Qlik Luminaries and Partner Ambassadors. With new people joining every year, this global network keeps growing, but one thing never changes: these folks bring the spark.

Over the past few weeks, I’ve spoken with a number of leaders who are digesting Salesforce’s move to acquire Informatica and what it will mean for them. If you are doing the same, I get it. Informatica has been an established company but in recent years pushing customers to move to their cloud only platform, will this accelerate this in particular with their recent PowerCenter end-of-support news?

As there are many questions to answer, we have split this blog in two parts. In part 1 of this blog, we explored how Qlik is using data and insight to drive decisions and actions. In this second part, we will focus on how to overcome the challenges along the way and set up for success for the future.

If you’re leading a data, analytics, or AI initiative right now, you know the pressure. AI is no longer a future project - it’s a business imperative. Executives want results, boards want differentiation, and the window to deliver is closing fast. That’s why Salesforce’s intent to acquire Informatica should raise serious questions for data leaders. Not just because of what it means for Informatica, but for what it could mean for your AI roadmap.

As enterprises double down on AI, there’s a hard truth many leaders are starting to face — they’ve invested in the promise of AI, but they can’t always trust the data behind the predictions. Whether you're training a model, building RAG pipelines, or scaling intelligent automation, AI outcomes are only as reliable as the data feeding them. Yet most organizations still can’t answer a critical question with confidence: Is our data truly AI-ready?

Welcome back to our ongoing series on strategies for gaining an unfair advantage. So far, we’ve explored how leveraging the tech ecosystem, overcoming adversity, unlocking hidden value in data, fostering great partnerships, and balancing risk with reward can set your organization apart. Each topic has offered actionable insights and real-world examples to help you stay ahead.